5 research outputs found
Pesquisa Nacional de Saúde 2019: histórico, métodos e perspectivas
This article presents the history and construction of the National Health Survey (PNS) 2019, a household survey conducted in partnership with the Brazilian Institute of Geography and Statistics. The objective was to provide the country with information on the determinants, conditions and health needs of the Brazilian population. The expected sample was 108,525 households, considering a non-response rate of 20%. The questionnaire had three parts: (i) regarding the household; (ii) to all residents of the household, focusing on the collection of socioeconomic and health information; and (iii) aimed at the selected resident (15 years or more) for whom lifestyles, chronic diseases, violence, among other topics were investigated, and anthropometric measures (sub-sample) were measured. The PNS information will serve as a basis for the (re)formulation of health policies, as well as support for existing actions and programs of the Unified Health System.Este artigo apresenta o histórico e a construção da Pesquisa Nacional de Saúde (PNS) 2019, inquérito de base domiciliar realizado em parceria com a fundação Instituto Brasileiro de Geografia e Estatística. O objetivo da PNS 2019 foi dotar o país de informações sobre os determinantes, condicionantes e necessidades de saúde da população brasileira. A amostra prevista foi de 108.525 domicílios particulares, considerando-se uma taxa de não resposta de 20%. Seu questionário continha três partes, orientadas para (i) o domicílio, (ii) todos os moradores do domicílio, com enfoque na coleta de informações socioeconômicas e de saúde, e (iii) o morador selecionado (idade ≥15 anos), sobre o qual investigou-se estilos de vida, doenças crônicas, violências, entre outros temas, e aferiu-se medidas antropométricas (subamostra). As informações da PNS 2019 servirão de base para a (re)formulação de políticas de saúde e subsídio a ações e programas existentes do Sistema Único de Saúde
Using active learning strategies during a quality improvement collaborative: exploring educational games to enhance learning among healthcare professionals
Background The Breakthrough Series model uses learning sessions (LS) to promote education, professional development and quality improvement (QI) in healthcare. Staff divergences regarding prior knowledge, previous experience, preferences and motivations make selecting which pedagogic strategies to use in LS a challenge.Aim We aimed to assess new active-learning strategies: two educational games, a card game and an escape room-type game, for training in healthcare-associated infection prevention.Methods This descriptive case study evaluated the performance of educational strategies during a Collaborative to reduce healthcare-associated infections in Brazilian intensive care units (ICUs). A post-intervention survey was voluntarily offered to all participants in LS activities.Results Seven regional 2-day LS were held between October and December 2022 (six for adult ICUs and one for paediatric/neonatal ICUs). Of 194 institutions participating in a nationwide QI initiative, 193 (99.4%) participated in these activities, totalling 850 healthcare professionals. From these, 641 participants responded to the survey (75.4%). The post-intervention survey showed that the participants responded positively to the educational activities.Conclusion The participants perceived the various pedagogical strategies positively, which shows the value of a broad and diverse educational approach, customised to local settings and including game-based activities, to enhance learning among healthcare professionals
NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics
Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data
NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics
Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data